Gyles Glover1, Gerda Arts, David Wooff. 1. Centre for Public Mental Health, University of Durham, Elvet Riverside II, New Elvet, Durham DH1 3JT, UK. Gyles.Glover@durham.ac.uk
Abstract
BACKGROUND: Mathematical models relating rates of mental health care use to population characteristics such as social deprivation are widely used in both planning and researching mental health services. The models currently in wide use in England are based on data mostly derived from the 10-yearly population censuses. These are perceived to be out of date many years before new census data are available for their replacement. A new set of government deprivation monitoring statistics based mainly on annually updatable data has recently been developed. This study set out to produce a mental illness needs index based on these new data. METHODS: A series of regression models were tested using individual domain scores from the DETR Index of Multiple Deprivation and the Office of National Statistics area-type classification as independent variables to predict 1998/9 psychiatric admission rates for broad diagnostic groups for 8251 of the 8414 electoral wards in England as dependent variables. RESULTS: The distribution of admission numbers in wards showed a pattern of over-dispersion with an excessive number of zero values for conventional regression approaches. A two-stage 'hurdle' model was, thus, adopted, predicting first the likelihood that wards would produce any admissions and second the probable number. This produced satisfactory predictive power, with residual variance showing strong geographical patterns associated with administrative areas, probably arising from differential resourcing or idiosyncratic clinical practice. CONCLUSIONS: A website providing data on the various indicators has been provided and its uses are indicated.
BACKGROUND: Mathematical models relating rates of mental health care use to population characteristics such as social deprivation are widely used in both planning and researching mental health services. The models currently in wide use in England are based on data mostly derived from the 10-yearly population censuses. These are perceived to be out of date many years before new census data are available for their replacement. A new set of government deprivation monitoring statistics based mainly on annually updatable data has recently been developed. This study set out to produce a mental illness needs index based on these new data. METHODS: A series of regression models were tested using individual domain scores from the DETR Index of Multiple Deprivation and the Office of National Statistics area-type classification as independent variables to predict 1998/9 psychiatric admission rates for broad diagnostic groups for 8251 of the 8414 electoral wards in England as dependent variables. RESULTS: The distribution of admission numbers in wards showed a pattern of over-dispersion with an excessive number of zero values for conventional regression approaches. A two-stage 'hurdle' model was, thus, adopted, predicting first the likelihood that wards would produce any admissions and second the probable number. This produced satisfactory predictive power, with residual variance showing strong geographical patterns associated with administrative areas, probably arising from differential resourcing or idiosyncratic clinical practice. CONCLUSIONS: A website providing data on the various indicators has been provided and its uses are indicated.
Authors: Stephani L Hatch; Souci Frissa; Maria Verdecchia; Robert Stewart; Nicola T Fear; Abraham Reichenberg; Craig Morgan; Bwalya Kankulu; Jennifer Clark; Billy Gazard; Robert Medcalf; Matthew Hotopf Journal: BMC Public Health Date: 2011-11-11 Impact factor: 3.295
Authors: Simon de Lusignan; Rob Navarro; Tom Chan; Glenys Parry; Kim Dent-Brown; Tony Kendrick Journal: BMC Med Inform Decis Mak Date: 2011-10-13 Impact factor: 2.796
Authors: Stephani L Hatch; Charlotte Woodhead; Souci Frissa; Nicola T Fear; Maria Verdecchia; Robert Stewart; Abraham Reichenberg; Craig Morgan; Paul Bebbington; Sally McManus; Traolach Brugha; Bwalya Kankulu; Jennifer L Clark; Billy Gazard; Robert Medcalf; Matthew Hotopf Journal: PLoS One Date: 2012-12-12 Impact factor: 3.240
Authors: James B Kirkbride; Daniel Jackson; Jesus Perez; David Fowler; Francis Winton; Jeremy W Coid; Robin M Murray; Peter B Jones Journal: BMJ Open Date: 2013-02-11 Impact factor: 2.692
Authors: Diogo Costa; Aleksandra Matanov; Reamonn Canavan; Edina Gabor; Tim Greacen; Petra Vondráčková; Ulrike Kluge; Pablo Nicaise; Jacek Moskalewicz; José Manuel Díaz-Olalla; Christa Straßmayr; Martijn Kikkert; Joaquim J F Soares; Andrea Gaddini; Henrique Barros; Stefan Priebe Journal: BMC Health Serv Res Date: 2014-02-03 Impact factor: 2.655